Unraveling the link between sterol ester and colorectal cancer: a two-sample Mendelian randomization study 

Unraveling the link between sterol ester and colorectal cancer: a two-sample Mendelian randomization study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unraveling the link between sterol ester and colorectal cancer: a two-sample Mendelian randomization study Chuanyuan Liu, Junfeng Xie, Baolong Ye, Junqiao Zhong, Xin Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4369169/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Nov, 2024 Read the published version in BMC Cancer → Version 1 posted 10 You are reading this latest preprint version Abstract Background Several studies reported the sterol ester (SE), one subclass of subtype of cholesterol esters (CE), is associated with the incidence of Colorectal cancer (CRC). Nevertheless, the causal relationship of SE on CRC remains unknown. Methods A two-sample Mendelian randomization study was performed with the summary statistics of sterol ester (27:1/14:0) from the largest available genome-wide association study meta-analysis(n = 377277) conducted by FinnGen consortium. The summary data were obtained from UK Biobank repository (377673 cases and 372016 controls). And we used relative filter ( p < 5 x 10 − 6 and LD r 2 < 0.01) of instrumental variables to explore the causal effect and complete the sensitive analysis with the threshold p < 5 x 10 − 8 and LD r 2 < 0.01. Inverse variance weighted, MR-Egger, weighted median, Simple Mode and weighted model, were used to examine the causal association between SE (27:1/14:0) and CRC. Cochran’s Q statistics were used to quantify the heterogeneity of instrumental variables. Results The IVW results showed that SE (27:1/14:0) (OR = 1.004; 95% CI 1.002, 1.005; p < 0.001) have genetic causal relationship with CRC. The results of Weighted median, Weighted mode and Simple mode are all consistent with IVW models. Though, the result from the MR-Egger method (OR = 1.005; 95% CI 1.004, 1.009; p = 0.052) didn’t demonstrate a significant result. There was no heterogeneity, horizontal pleiotropy or outliers, and results were normally distributed. The MR analysis results were not driven by a single SNP. And results from two filter threshold is consistent. Conclusion Altogether, genetically predicted sterol ester (27:1/14:0) plays a causal association role in the incidence of CRC. This finding will provide a new screening and diagnosis indicator of CRC in the future. sterol ester causal genetic colorectal cancer mendelian randomization Figures Figure 1 1. INTRODUCTION Colorectal cancer (CRC) is a highly prevalent malignant tumor of the digestive tract, ranking third in incidence and becoming the leading cause of cancer-related death in men and the second leading cause in women recently[ 1 ]. In 2020, the annual number of new colorectal cancer cases reached 1.9 million, and presently, the incidence rate is even higher, significantly contributing to the global cancer burden[ 2 ]. Typically, significant delays occur from the onset of symptoms to the diagnosis of early-onset colorectal cancer cause the asymptomatic at the beginning[ 3 ]. Therefore, it is crucial to prevent the occurrence of colorectal cancer through targeted health interventions aimed at addressing its etiology. Colorectal cancer (CRC) is a multifactorial disease influenced by various risk factors, such as excess ethanol intake in alcoholic drinks[ 4 ], smoking[ 5 ], overweight[ 6 ], bacterial species[ 7 ] in gut including Fusobacterium nucleatum, enterotoxigenic Bacteroides fragilis, and pks + E. coli etc. Furthermore, certain lipid metabolism pathways are linked to an elevated risk of CRC[ 8 ]. And The disordered levels of lipids in colorectal cancer tissue and patient serum may be correlated with initiation of colorectal cancer[ 9 ]. Additionally, lipids such as phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin may serve as diagnostic markers for various stages of colorectal cancer[ 10 ]. Nevertheless, the association between lipids and CRC warrants further investigation and validation in a larger cohort. Sterol esters(SE)[ 11 ], is a subtype of cholesteryl ester (CE), are a group of lipids implicated in the onset and progression of CRC. Liu et al. examined the expression levels of enzymes associated with cholesteryl ester metabolism and found a strong correlation between the expression of enzymes involved in cholesteryl ester synthesis (ACAT1 and ACAT2) and the occurrence of CRC[ 12 ]. However, Sadek et al[ 13 ]. discovered that free-form plant sterol esters have been shown to inhibit colon cancer via suppressing inflammation and inducing apoptosis. Given the contentious association between sterol esters and CRC, additional investigations are warranted to elucidate this relationship. Mendelian randomization (MR) serves as an analytical method for making causal inferences within the realm of epidemiological etiology[ 14 ]. To unveil the causal relationship between the CRC and sterol ester (27:1/14:0), we conducted a two-sample Mendelian randomization utilizing methods including "MR-Egger," "Weighted median," "Inverse variance weighted," "Simple mode," and "Weighted mode." Genome-wide association studies (GWAS) have pinpointed numerous variants linked to diseases and traits located within noncoding regions of the genome.[ 15 ] By incorporating instrumental variables as genetic predictors, the causal relationship between genes and diseases remains unaffected by common confounding factors such as environmental influences, socioeconomic variables, and individual behaviors. Thus, this study is to investigate the causal relationship between the CRC and sterol ester (27:1/14:0) and provide some clinical helpful insights for the diagnosis of CRC patients. 2. METHODS 2.1 Exposures: Ottensmann et al. analysis We utilized data from Ottensmann et al.'s genome-wide association analysis of plasma lipidome, which identified 495 genetic associations with 179 lipids[ 16 ]. Ottensmann et al reported 11318730 sterol ester (27:1/14:0) associated genome-wide SNPs from 377277 FinnGen participants. Initially, we applied a threshold (p 0.01. Due to the limited number of SNPs, we set a relatively relaxed threshold (p 0.01 in the 5000-kb region to obtain enough IVs to do sensitivity analysis. 2.2 Outcomes Summary statistics of CRC were obtained from a GWAS comprising 377673 cases and 372016 controls of European population[ 17 ]. Our exposure and outcome population samples did not overlap. We use the significant independent sterol ester (27:1/14:0) associated SNPs to assess the causal effect between CRC and sterol ester (27:1/14:0). All of the SNPs are available in the Summary data of CRC. The SNPs were used as IVs to perform the MR analysis (Supplementary Table 1). Ethical approval was obtained for each of the original GWAS, and detailed information can be found in the respective publications. 2.3 MR analysis To investigate the causal relationship via the MR analysis, the IVs should satisfied the three assumptions[ 18 ]: (1) the selected IVs should be directly associated with sterol ester (27:1/14:0); (2) the selected IVs should not be associated with confounders;(3) the selected IVs must exert no effects on the CRC other than through the sterol ester (27:1/14:0) (Instrument Strength Independent of Direct Effect (INSIDE) assumption). We utilized the classic Inverse Variance Weighted model (IVW) to perform the primary MR analysis, known for providing a stable and accurate assessment of causal relationships in the absence of directional pleiotropy[ 19 , 20 ]. Furthermore, MR-Egger regression, Weighted Median (WM), Simple Mode, and Weighted Mode were employed as complementary methods to evaluate the causal effect. Under the INSIDE assumption, the MR-Egger method can estimate the horizontal average pleiotropic effect by conducting a weighted linear regression that relies on instrument strength independent of direct effects[ 18 , 21 ]. The WM method plays a crucial role when the majority of genetic variants are invalid. It allows for obtaining a robust overall causal estimate, ensuring reliability even in the presence of invalid variants[ 22 ]. The Simple Mode and Weighted Mode are both mode-based methods, capable of estimating the causal effect of individual SNPs to form clusters. To elaborate, the Simple Mode selects the causal estimation from the largest cluster of SNPs, while the Weighted Mode assigns weights to each SNP[ 23 ]. The TwoSampleMR package (version 0.5.10) in R (version 4.2.3) was utilized to conduct the five MR methods. 2.4 Pleiotropy, heterogeneity, and sensitivity evaluation The results from all five methods are required same directions, with p-values less than 0.05 indicating significance. We used the MR-Egger method to return intercept values for testing horizontal pleiotropy. Cochran’s Q statistic from IVW was taken as the assessment of heterogeneity. We also performed Leave-one-out and single SNP analyses to determine if a single SNP was driving the causal estimates. Additionally, another MR analysis was conducted with a stricter threshold of p < 5 x 10 − 8 ) and LD with r 2 < 0.01 for the complement of sensitivity analysis (supplementary materials). 3. Results After filtering of the SNPs from the Finngen at a genome-wide significance threshold of p < 5 x 10 − 6 and LD r 2 < 0.01, 14 SNPs associated with sterol ester (27:1/14:0) were identified (supplementary table 1 ). We conducted random-effects IVW models, along with two-sample MR analyses, utilizing these SNPs as instruments. The results indicate a genetically predicted causal effect of sterol ester on the risk of CRC (OR = 1.004; 95% CI 1.002, 1.005; p < 0.001) (Fig. 1 A- 1 C). Though, the result from the MR-Egger method (OR = 1.005; 95% CI 1.004, 1.009; p = 0.052) didn’t demonstrate a significant result (supplementary table 2 ). The results of Weighted median, Weighted mode, and Simple mode are all consistent with IVW models (Table). There was no heterogeneity observed among the selected SNPs, as demonstrated by both the MR-Egger (Cochran’s Q = 9.951; p = 0.620) and IVW methods (Cochran’s Q = 10.089; P = 0.687). Additionally, MR-Egger analysis was conducted to assess horizontal pleiotropy among the selected SNPs, revealing no evidence of pleiotropy (β intercept = -8.63E-05; SE = 0.000233; p = 0.717) influencing the results (Figure). The leave-one-out sensitivity analysis revealed that the causal association between sterol ester (27:1/14:0) and CRC is not driven by a single SNP (Fig. 1 D). The associations of each variant with sterol ester and the risk of CRC are depicted in Figure S3. 4. Disscussion In this study, a two-sample MR analysis was conducted using European GWAS data to investigate the relationship between CRC and sterol ester (27:1/14:0). Our findings indicate that sterol ester (27:1/14:0) exhibits a causal effect on CRC risk. To validate the conclusion, an MR analysis was also conducted using the 2 instrumental variables (IVs) meeting the threshold criteria ( p < 5 x 10 − 8 and LD r 2 < 0.01). We employed the IVW method and obtained a similar result (OR = 1.007; 95% CI 1.002, 1.11; p = 0.007), reinforcing the same conclusion (supplementary materials). Sterol ester (27:1/14:0), as a subtype of cholesterol esters, has been demonstrated to be associated with CRC[ 24 , 25 ]. In a study conducted by Bershteĭn et al[ 24 ]. on CRC tissue, they observed a significant increase in cholesterol esters among CRC patients. Additionally, Munir et al[ 25 ]. compared isogenic primary and metastatic colon cancer cell lines and observed that, compared to SW480, CE content is significantly decreased in SW620 cells. This suggests that CE may play an important role in CRC progression. Enzymes involved in CE metabolism are strongly correlated with the pathogenesis, progression, and heterogeneity of CRC[ 12 ]. However, the precise causal relationship between sterol ester (27:1/14:0) and CRC, which could be beneficial for CRC diagnosis, remains unclear. There is some experimental evidence for the association between sterol ester and CRC. In a previous study, adenomatous polyposis coli mice were fed with plant sterol ester, revealing that a high intake of plant sterol ester accelerates intestinal tumorigenesis in females. Gene expression analysis from the mucosa of the small intestine illustrated up-regulated genes associated with cell cycle control and cholesterol biosynthesis in female mice fed with plant sterol ester[ 26 ]. Sterol ester (27:1/14:0) may influence the cell cycle of epithelial cells, potentially leading to the development of CRC. This study explores the cause relationship between sterol ester (27:1/14:0) and CRC without via MR methods. All the methods indicate a significant result except MR-Egger method while MR-Egger analysis revealed no evidence of pleiotropy (β intercept = -8.63E-05; SE = 0.000233; p = 0.717). Thus, the non-significant from MR-Egger may due to the limited number of samples. In addition, all the SNPs were filter at the threshold of p < 5 x 10 − 6 and LD r 2 < 0.01, indicating a lower likelihood of weak instrument bias. And the MR result from the threshold of p < 5 x 10 − 8 and LD r 2 < 0.01 is consist with the previous one which is further decrease potential the bias. What’s more, we used several approaches to assess the sensitive and pleiotropy, indicating the similar result. Nonetheless, this study has some limitations that need to be acknowledged. Firstly, all SNP data are from European cohorts, and further validation of our findings is needed in other ethnicities. Additionally, we employed a relatively relaxed threshold (p < 5 x 10 − 6 and LD r 2 < 0.01), as only 2 SNPs were identified under the more stringent criteria of p < 5 x 10 − 8 and LD r 2 < 0.01. Furthermore, the experimental validation is warrant for the causal relationship between sterol ester (27:1/14:0). Altogether, the association between genetically predicted sterol ester (27:1/14:0) and CRC has been established. This finding will contribute to the screening and diagnosis of CRC in the future. Abbreviations SE, sterol ester; CE, cholesterol esters; CRC, Colorectal cancer, LD, linkage disequilibrium, IVW, Variance Weighted model; WM, Weighted Median; IVs, instrumental variables. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials The datasets analyzed during the current study are available in the FinnGen repository (https://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90277001-GCST90278000/GCST90277238/) and the UK Biobank repository, https://gwas.mrcieu.ac.uk/datasets/ieu-b-4965/. Competing interests The authors hereby declare that they have no conflicts of interest to disclose. Funding None Authors' contributions CYL: Methodology, data curation, formal analysis, visualization, original draft writing. JFX, BLY, JQZ: revised the manuscript, and XX: design of the work. All authors reviewed the manuscript. Acknowledgements We would like to express our gratitude to the participants and investigators involved in the FinnGen study, as well as the collaborators of the UK Biobank. References Siegel RL, Giaquinto AN, Jemal A. Cancer Stat 2024 CA: cancer J Clin. 2024;74(1):12–49. Sung H, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. Cancer J Clin. 2021;71(3):209–49. Patel SG, et al. The rising tide of early-onset colorectal cancer: a comprehensive review of epidemiology, clinical features, biology, risk factors, prevention, and early detection. The lancet. Gastroenterol Hepatol. 2022;7(3):262–74. Vieira AR, et al. Foods and beverages and colorectal cancer risk: a systematic review and meta-analysis of cohort studies, an update of the evidence of the WCRF-AICR Continuous Update Project. Annals oncology: official J Eur Soc Med Oncol. 2017;28(8):1788–802. Botteri E, et al. Smoking and colorectal cancer: a meta-analysis. JAMA. 2008;300(23):2765–78. Kyrgiou M et al. Adiposity and cancer at major anatomical sites: umbrella review of the literature. BMJ (Clinical research ed.), 2017. 356: p. j477. Dougherty MW, Jobin C. Intestinal bacteria and colorectal cancer: etiology and treatment. Gut Microbes. 2023;15(1):2185028. O'Keefe SJD. Diet, microorganisms and their metabolites, and colon cancer. Nat Rev Gastroenterol Hepatol. 2016;13(12):691–706. Zhang X, et al. Lipid levels in serum and cancerous tissues of colorectal cancer patients. World J Gastroenterol. 2014;20(26):8646–52. Elmallah MIY, et al. Lipidomic profiling of exosomes from colorectal cancer cells and patients reveals potential biomarkers. Mol Oncol. 2022;16(14):2710–8. Lampe MA, et al. Human stratum corneum lipids: characterization and regional variations. J Lipid Res. 1983;24(2):120–30. Liu Z, et al. Correlation of cholesteryl ester metabolism to pathogenesis, progression and disparities in colorectal Cancer. Lipids Health Dis. 2022;21(1):22. Sadek NF, et al. Plant Sterol Esters in Extruded Food Model Inhibits Colon Carcinogenesis by Suppressing Inflammation and Stimulating Apoptosis. J Med Food. 2017;20(7):659–66. Smith GD, Ebrahim S. 'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? 2003. p. 1–22. Farh KK, et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature. 2015;518(7539):337–43. Ottensmann L, et al. Genome-wide association analysis of plasma lipidome identifies 495 genetic associations. Nat Commun. 2023;14(1):6934. Tassi A, Mavromatis I, Piechocki RJR. A dataset of full-stack ITS-G5 DSRC communications over licensed and unlicensed bands using a large-scale urban testbed. Data brief. 2019;25:104368. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512–25. Burgess S, Dudbridge F, Thompson SG. Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Stat Med. 2016;35(11):1880–906. Burgess S, et al. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol. 2015;30(7):543–52. Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32(5):377–89. Bowden J, et al. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet Epidemiol. 2016;40(4):304–14. Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int J Epidemiol. 2017;46(6):1985–98. Bershteĭn LM, et al. [Content of cyclic nucleotides, cholesterol and phospholipids in tumors of the large intestine]. Vopr Onkol. 1985;31(2):50–4. Munir R, et al. Abundance, fatty acid composition and saturation index of neutral lipids in colorectal cancer cell lines. Acta Biochim Pol. 2021;68(1):115–8. Marttinen M, et al. Plant sterol feeding induces tumor formation and alters sterol metabolism in the intestine of Apc(Min) mice. Nutr Cancer. 2014;66(2):259–69. Additional Declarations No competing interests reported. Supplementary Files Supplementarytables.xlsx suplementaryFigure.docx Cite Share Download PDF Status: Published Journal Publication published 27 Nov, 2024 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 19 Aug, 2024 Reviews received at journal 18 Aug, 2024 Reviewers agreed at journal 08 Aug, 2024 Reviews received at journal 25 Jul, 2024 Reviewers agreed at journal 21 Jul, 2024 Reviewers invited by journal 13 May, 2024 Editor invited by journal 13 May, 2024 Editor assigned by journal 10 May, 2024 Submission checks completed at journal 10 May, 2024 First submitted to journal 04 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4369169","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":304027597,"identity":"f133f08b-b6f8-4a8b-b98c-57a9f2b24f16","order_by":0,"name":"Chuanyuan Liu","email":"","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chuanyuan","middleName":"","lastName":"Liu","suffix":""},{"id":304027598,"identity":"669476bf-4e9d-4fc9-bda5-c88cf95d5139","order_by":1,"name":"Junfeng Xie","email":"","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junfeng","middleName":"","lastName":"Xie","suffix":""},{"id":304027599,"identity":"c2ea0fed-0c39-461e-b9ba-148a075951da","order_by":2,"name":"Baolong Ye","email":"","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Baolong","middleName":"","lastName":"Ye","suffix":""},{"id":304027600,"identity":"5f070280-7a10-435c-8101-e67c02f0f688","order_by":3,"name":"Junqiao Zhong","email":"","orcid":"","institution":"Ganzhou People's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junqiao","middleName":"","lastName":"Zhong","suffix":""},{"id":304027601,"identity":"40709b19-2886-42f9-ba21-ec25b1664c2d","order_by":4,"name":"Xin Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie3RvYrCQBDA8Q0DYzNn2pGT+AorQiofZoOSSiFlCuGESFL49QY+g6WlIqzNXm+pb6DdXeOd1oobO4v91ftnZlghHOcNYSXb/Z4Iv3KAzUGlA3tSJa0+uV71ZhXsyIPR9iTgnmRqB97Cp7B2HEGJxchIyb0QEDBOoyEKvxgryy15ohITIwLofbSqCzbfS8uU7XJdm2i6TdlHBoXkviVh1Rx+XP4YgcIkyqFM0m0JIpS3RJRLSMfAhOq6WIeV0WS9pVFk2rt+pWrMt5vzTzoI/GL6PLlDrz13HMdxHvoHGV9AmEt+POQAAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of University of South China","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-05-04 16:24:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4369169/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4369169/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-024-13228-z","type":"published","date":"2024-11-27T15:57:39+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":56888449,"identity":"3066a9f8-bfa2-4926-9b7c-2b68c422474b","added_by":"auto","created_at":"2024-05-21 19:01:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":430232,"visible":true,"origin":"","legend":"\u003cp\u003eSNP effect evaluation in TSMR between CRC and sterol ester (27:1/14:0). (A) MR test scatter plot of five methods. The x-axis is the SNP effect on sterol ester (27:1/14:0). The y-axis is the SNP effect on CRC. (B) MR funnel plot of IVW and MR-Egger methods. (C) Forest plot of MR sensitivity analysis. All MR-Egger and IVM methods showed that MR effect sizes that are larger than 0 mean that sterol ester (27:1/14:0) had a causal effect on CRC. (D) Forest plot of MR leave-one-out sensitivity analysis. MR, Mendelian randomization; SNP, single-nucleotide polymorphism.\u003c/p\u003e","description":"","filename":"fIg1.png","url":"https://assets-eu.researchsquare.com/files/rs-4369169/v1/69c10f6df04c5ffa6eafed57.png"},{"id":70382729,"identity":"22e22832-afad-4a63-ae3e-c6d1329dcac5","added_by":"auto","created_at":"2024-12-02 16:29:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":808173,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4369169/v1/f92db0b0-6084-43c9-a622-26ecc1363e3e.pdf"},{"id":56888451,"identity":"f8d21157-2d09-437c-b891-4c14ba7a844a","added_by":"auto","created_at":"2024-05-21 19:01:57","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17859,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4369169/v1/667c23cdecb07b67899bd9cd.xlsx"},{"id":56888450,"identity":"f0a17619-6abc-45a5-adaf-56984ce208c0","added_by":"auto","created_at":"2024-05-21 19:01:57","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":237862,"visible":true,"origin":"","legend":"","description":"","filename":"suplementaryFigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-4369169/v1/d2763f40cc904c8660f8ba92.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unraveling the link between sterol ester and colorectal cancer: a two-sample Mendelian randomization study ","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eColorectal cancer (CRC) is a highly prevalent malignant tumor of the digestive tract, ranking third in incidence and becoming the leading cause of cancer-related death in men and the second leading cause in women recently[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In 2020, the annual number of new colorectal cancer cases reached 1.9\u0026nbsp;million, and presently, the incidence rate is even higher, significantly contributing to the global cancer burden[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Typically, significant delays occur from the onset of symptoms to the diagnosis of early-onset colorectal cancer cause the asymptomatic at the beginning[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, it is crucial to prevent the occurrence of colorectal cancer through targeted health interventions aimed at addressing its etiology.\u003c/p\u003e \u003cp\u003eColorectal cancer (CRC) is a multifactorial disease influenced by various risk factors, such as excess ethanol intake in alcoholic drinks[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], smoking[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], overweight[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], bacterial species[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] in gut including Fusobacterium nucleatum, enterotoxigenic Bacteroides fragilis, and pks\u0026thinsp;+\u0026thinsp;E. coli etc. Furthermore, certain lipid metabolism pathways are linked to an elevated risk of CRC[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. And The disordered levels of lipids in colorectal cancer tissue and patient serum may be correlated with initiation of colorectal cancer[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, lipids such as phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin may serve as diagnostic markers for various stages of colorectal cancer[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Nevertheless, the association between lipids and CRC warrants further investigation and validation in a larger cohort. Sterol esters(SE)[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], is a subtype of cholesteryl ester (CE), are a group of lipids implicated in the onset and progression of CRC. Liu et al. examined the expression levels of enzymes associated with cholesteryl ester metabolism and found a strong correlation between the expression of enzymes involved in cholesteryl ester synthesis (ACAT1 and ACAT2) and the occurrence of CRC[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, Sadek et al[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. discovered that free-form plant sterol esters have been shown to inhibit colon cancer via suppressing inflammation and inducing apoptosis. Given the contentious association between sterol esters and CRC, additional investigations are warranted to elucidate this relationship.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) serves as an analytical method for making causal inferences within the realm of epidemiological etiology[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. To unveil the causal relationship between the CRC and sterol ester (27:1/14:0), we conducted a two-sample Mendelian randomization utilizing methods including \"MR-Egger,\" \"Weighted median,\" \"Inverse variance weighted,\" \"Simple mode,\" and \"Weighted mode.\" Genome-wide association studies (GWAS) have pinpointed numerous variants linked to diseases and traits located within noncoding regions of the genome.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] By incorporating instrumental variables as genetic predictors, the causal relationship between genes and diseases remains unaffected by common confounding factors such as environmental influences, socioeconomic variables, and individual behaviors. Thus, this study is to investigate the causal relationship between the CRC and sterol ester (27:1/14:0) and provide some clinical helpful insights for the diagnosis of CRC patients.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Exposures: Ottensmann et al. analysis\u003c/h2\u003e \u003cp\u003eWe utilized data from Ottensmann et al.'s genome-wide association analysis of plasma lipidome, which identified 495 genetic associations with 179 lipids[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Ottensmann et al reported 11318730 sterol ester (27:1/14:0) associated genome-wide SNPs from 377277 FinnGen participants. Initially, we applied a threshold (p\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e) to identify independent SNPs. Subsequently, we clustered the SNPs within a 5000-kb region based on linkage disequilibrium (LD) with an r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.01. Due to the limited number of SNPs, we set a relatively relaxed threshold (p\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e) and clumped LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.01 in the 5000-kb region to obtain enough IVs to do sensitivity analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Outcomes\u003c/h2\u003e \u003cp\u003eSummary statistics of CRC were obtained from a GWAS comprising 377673 cases and 372016 controls of European population[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Our exposure and outcome population samples did not overlap.\u003c/p\u003e \u003cp\u003eWe use the significant independent sterol ester (27:1/14:0) associated SNPs to assess the causal effect between CRC and sterol ester (27:1/14:0). All of the SNPs are available in the Summary data of CRC. The SNPs were used as IVs to perform the MR analysis (Supplementary Table\u0026nbsp;1). Ethical approval was obtained for each of the original GWAS, and detailed information can be found in the respective publications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 MR analysis\u003c/h2\u003e \u003cp\u003eTo investigate the causal relationship via the MR analysis, the IVs should satisfied the three assumptions[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]: (1) the selected IVs should be directly associated with sterol ester (27:1/14:0); (2) the selected IVs should not be associated with confounders;(3) the selected IVs must exert no effects on the CRC other than through the sterol ester (27:1/14:0) (Instrument Strength Independent of Direct Effect (INSIDE) assumption).\u003c/p\u003e \u003cp\u003eWe utilized the classic Inverse Variance Weighted model (IVW) to perform the primary MR analysis, known for providing a stable and accurate assessment of causal relationships in the absence of directional pleiotropy[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, MR-Egger regression, Weighted Median (WM), Simple Mode, and Weighted Mode were employed as complementary methods to evaluate the causal effect. Under the INSIDE assumption, the MR-Egger method can estimate the horizontal average pleiotropic effect by conducting a weighted linear regression that relies on instrument strength independent of direct effects[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The WM method plays a crucial role when the majority of genetic variants are invalid. It allows for obtaining a robust overall causal estimate, ensuring reliability even in the presence of invalid variants[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The Simple Mode and Weighted Mode are both mode-based methods, capable of estimating the causal effect of individual SNPs to form clusters. To elaborate, the Simple Mode selects the causal estimation from the largest cluster of SNPs, while the Weighted Mode assigns weights to each SNP[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe TwoSampleMR package (version 0.5.10) in R (version 4.2.3) was utilized to conduct the five MR methods.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Pleiotropy, heterogeneity, and sensitivity evaluation\u003c/h2\u003e \u003cp\u003eThe results from all five methods are required same directions, with p-values less than 0.05 indicating significance. We used the MR-Egger method to return intercept values for testing horizontal pleiotropy. Cochran\u0026rsquo;s Q statistic from IVW was taken as the assessment of heterogeneity. We also performed Leave-one-out and single SNP analyses to determine if a single SNP was driving the causal estimates. Additionally, another MR analysis was conducted with a stricter threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e) and LD with r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for the complement of sensitivity analysis (supplementary materials).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eAfter filtering of the SNPs from the Finngen at a genome-wide significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e and LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 14 SNPs associated with sterol ester (27:1/14:0) were identified (supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We conducted random-effects IVW models, along with two-sample MR analyses, utilizing these SNPs as instruments. The results indicate a genetically predicted causal effect of sterol ester on the risk of CRC (OR\u0026thinsp;=\u0026thinsp;1.004; 95% CI 1.002, 1.005; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Though, the result from the MR-Egger method (OR\u0026thinsp;=\u0026thinsp;1.005; 95% CI 1.004, 1.009; p\u0026thinsp;=\u0026thinsp;0.052) didn\u0026rsquo;t demonstrate a significant result (supplementary table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results of Weighted median, Weighted mode, and Simple mode are all consistent with IVW models (Table). There was no heterogeneity observed among the selected SNPs, as demonstrated by both the MR-Egger (Cochran\u0026rsquo;s Q\u0026thinsp;=\u0026thinsp;9.951; p\u0026thinsp;=\u0026thinsp;0.620) and IVW methods (Cochran\u0026rsquo;s Q\u0026thinsp;=\u0026thinsp;10.089; P\u0026thinsp;=\u0026thinsp;0.687). Additionally, MR-Egger analysis was conducted to assess horizontal pleiotropy among the selected SNPs, revealing no evidence of pleiotropy (β intercept = -8.63E-05; SE\u0026thinsp;=\u0026thinsp;0.000233; p\u0026thinsp;=\u0026thinsp;0.717) influencing the results (Figure). The leave-one-out sensitivity analysis revealed that the causal association between sterol ester (27:1/14:0) and CRC is not driven by a single SNP (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). The associations of each variant with sterol ester and the risk of CRC are depicted in Figure S3.\u003c/p\u003e"},{"header":"4. Disscussion","content":"\u003cp\u003eIn this study, a two-sample MR analysis was conducted using European GWAS data to investigate the relationship between CRC and sterol ester (27:1/14:0). Our findings indicate that sterol ester (27:1/14:0) exhibits a causal effect on CRC risk. To validate the conclusion, an MR analysis was also conducted using the 2 instrumental variables (IVs) meeting the threshold criteria (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e and LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). We employed the IVW method and obtained a similar result (OR\u0026thinsp;=\u0026thinsp;1.007; 95% CI 1.002, 1.11; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007), reinforcing the same conclusion (supplementary materials).\u003c/p\u003e \u003cp\u003eSterol ester (27:1/14:0), as a subtype of cholesterol esters, has been demonstrated to be associated with CRC[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In a study conducted by Bershteĭn et al[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. on CRC tissue, they observed a significant increase in cholesterol esters among CRC patients. Additionally, Munir et al[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. compared isogenic primary and metastatic colon cancer cell lines and observed that, compared to SW480, CE content is significantly decreased in SW620 cells. This suggests that CE may play an important role in CRC progression. Enzymes involved in CE metabolism are strongly correlated with the pathogenesis, progression, and heterogeneity of CRC[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, the precise causal relationship between sterol ester (27:1/14:0) and CRC, which could be beneficial for CRC diagnosis, remains unclear.\u003c/p\u003e \u003cp\u003eThere is some experimental evidence for the association between sterol ester and CRC. In a previous study, adenomatous polyposis coli mice were fed with plant sterol ester, revealing that a high intake of plant sterol ester accelerates intestinal tumorigenesis in females. Gene expression analysis from the mucosa of the small intestine illustrated up-regulated genes associated with cell cycle control and cholesterol biosynthesis in female mice fed with plant sterol ester[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Sterol ester (27:1/14:0) may influence the cell cycle of epithelial cells, potentially leading to the development of CRC.\u003c/p\u003e \u003cp\u003eThis study explores the cause relationship between sterol ester (27:1/14:0) and CRC without via MR methods. All the methods indicate a significant result except MR-Egger method while MR-Egger analysis revealed no evidence of pleiotropy (β intercept = -8.63E-05; SE\u0026thinsp;=\u0026thinsp;0.000233; p\u0026thinsp;=\u0026thinsp;0.717). Thus, the non-significant from MR-Egger may due to the limited number of samples. In addition, all the SNPs were filter at the threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e and LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, indicating a lower likelihood of weak instrument bias. And the MR result from the threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e and LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 is consist with the previous one which is further decrease potential the bias. What\u0026rsquo;s more, we used several approaches to assess the sensitive and pleiotropy, indicating the similar result.\u003c/p\u003e \u003cp\u003eNonetheless, this study has some limitations that need to be acknowledged. Firstly, all SNP data are from European cohorts, and further validation of our findings is needed in other ethnicities. Additionally, we employed a relatively relaxed threshold (p\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e and LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as only 2 SNPs were identified under the more stringent criteria of p\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e and LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Furthermore, the experimental validation is warrant for the causal relationship between sterol ester (27:1/14:0).\u003c/p\u003e \u003cp\u003eAltogether, the association between genetically predicted sterol ester (27:1/14:0) and CRC has been established. This finding will contribute to the screening and diagnosis of CRC in the future.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSE, sterol ester; CE, cholesterol esters; CRC, Colorectal cancer, LD, linkage disequilibrium, IVW, Variance Weighted model; WM, Weighted Median; IVs, instrumental variables.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003eThe datasets analyzed during the current study are available in the FinnGen repository (https://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90277001-GCST90278000/GCST90277238/) and the UK Biobank repository, https://gwas.mrcieu.ac.uk/datasets/ieu-b-4965/.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors hereby declare that they have no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCYL: Methodology, data curation, formal analysis, visualization, original draft writing.\u0026nbsp;JFX,\u0026nbsp;BLY, JQZ: revised the manuscript, and XX: design of the work. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our gratitude to the participants and investigators involved in the FinnGen study, as well as the collaborators of the UK Biobank.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSiegel RL, Giaquinto AN, Jemal A. Cancer Stat 2024 CA: cancer J Clin. 2024;74(1):12\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSung H, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. Cancer J Clin. 2021;71(3):209\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel SG, et al. The rising tide of early-onset colorectal cancer: a comprehensive review of epidemiology, clinical features, biology, risk factors, prevention, and early detection. The lancet. 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Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol. 2015;30(7):543\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32(5):377\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBowden J, et al. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet Epidemiol. 2016;40(4):304\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int J Epidemiol. 2017;46(6):1985\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBershteĭn LM, et al. [Content of cyclic nucleotides, cholesterol and phospholipids in tumors of the large intestine]. Vopr Onkol. 1985;31(2):50\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMunir R, et al. Abundance, fatty acid composition and saturation index of neutral lipids in colorectal cancer cell lines. Acta Biochim Pol. 2021;68(1):115\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarttinen M, et al. Plant sterol feeding induces tumor formation and alters sterol metabolism in the intestine of Apc(Min) mice. Nutr Cancer. 2014;66(2):259\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"sterol ester, causal, genetic, colorectal cancer, mendelian randomization","lastPublishedDoi":"10.21203/rs.3.rs-4369169/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4369169/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSeveral studies reported the sterol ester (SE), one subclass of subtype of cholesterol esters (CE), is associated with the incidence of Colorectal cancer (CRC). Nevertheless, the causal relationship of SE on CRC remains unknown.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA two-sample Mendelian randomization study was performed with the summary statistics of sterol ester (27:1/14:0) from the largest available genome-wide association study meta-analysis(n\u0026thinsp;=\u0026thinsp;377277) conducted by FinnGen consortium. The summary data were obtained from UK Biobank repository (377673 cases and 372016 controls). And we used relative filter (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e and LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) of instrumental variables to explore the causal effect and complete the sensitive analysis with the threshold \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e and LD r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Inverse variance weighted, MR-Egger, weighted median, Simple Mode and weighted model, were used to examine the causal association between SE (27:1/14:0) and CRC. Cochran\u0026rsquo;s Q statistics were used to quantify the heterogeneity of instrumental variables.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe IVW results showed that SE (27:1/14:0) (OR\u0026thinsp;=\u0026thinsp;1.004; 95% CI 1.002, 1.005; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) have genetic causal relationship with CRC. The results of Weighted median, Weighted mode and Simple mode are all consistent with IVW models. Though, the result from the MR-Egger method (OR\u0026thinsp;=\u0026thinsp;1.005; 95% CI 1.004, 1.009; p\u0026thinsp;=\u0026thinsp;0.052) didn\u0026rsquo;t demonstrate a significant result. There was no heterogeneity, horizontal pleiotropy or outliers, and results were normally distributed. The MR analysis results were not driven by a single SNP. And results from two filter threshold is consistent.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAltogether, genetically predicted sterol ester (27:1/14:0) plays a causal association role in the incidence of CRC. This finding will provide a new screening and diagnosis indicator of CRC in the future.\u003c/p\u003e","manuscriptTitle":"Unraveling the link between sterol ester and colorectal cancer: a two-sample Mendelian randomization study ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-21 19:01:53","doi":"10.21203/rs.3.rs-4369169/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-19T19:53:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-18T15:25:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76338053837646741025284057291553967551","date":"2024-08-08T14:00:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-25T17:55:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196902294705957452371235442578718935133","date":"2024-07-21T15:32:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-13T15:44:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-13T11:52:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-10T07:19:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-10T07:19:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2024-05-04T16:15:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ffb5ffd1-c413-45a8-967b-5498da4dd07c","owner":[],"postedDate":"May 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T16:02:34+00:00","versionOfRecord":{"articleIdentity":"rs-4369169","link":"https://doi.org/10.1186/s12885-024-13228-z","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2024-11-27 15:57:39","publishedOnDateReadable":"November 27th, 2024"},"versionCreatedAt":"2024-05-21 19:01:53","video":"","vorDoi":"10.1186/s12885-024-13228-z","vorDoiUrl":"https://doi.org/10.1186/s12885-024-13228-z","workflowStages":[]},"version":"v1","identity":"rs-4369169","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4369169","identity":"rs-4369169","version":["v1"]},"buildId":"ehx78VzkSd0WSzXnipQa-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}